RESEARCH ARTICLE

Factors determining cognitive, motor and

language scores in low birth weight infants

from North India

Ravi Prakash UpadhyayID1,2*, Sunita Taneja1, Suman Ranjitkar3, Sarmila Mazumder1,

Nita Bhandari1, Tarun Dua4, Laxman Shrestha3, Tor A. Strand5

1 Centre for Health Research and Development, Society for Applied Studies, New Delhi, India, 2 Department

of Global Public Health and Primary Care, University of Bergen, Bergen, Norway, 3 Department of Child

Health, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal, 4 Department of Mental Health and

Substance Abuse, World Health Organization, Geneva, Switzerland, 5 Department of Research, Innlandet

Hospital Trust, Lillehammer, Norway

* ravi.upadhyay@sas.org.in

Abstract

Background

Children born with low birth weight (LBW) tend to have lower neurodevelopmental scores

compared to term normal birth weight children. It is important to determine factors that influ-

ence neurodevelopment in these low birth weight children especially in the first 2–3 years of

life that represents a period of substantial brain development.

Methods

This secondary data analysis was conducted using data from LBW infants enrolled soon

after birth in an individually randomized controlled trial (RCT) and followed up till end of 1st

year. Neurodevelopmental assessment was done at 12 months of corrected age by trained

psychologists using Bayley Scales of Infant and Toddler Development 3rd edition (Bayley-

III). Factors influencing cognitive, motor and language scores were determined using multi-

variable linear regression model.

Results

Linear growth (i.e., length for age z score, LAZ) [cognitive: Standardized β-coefficient =

2.19, 95% CI; 1.29, 3.10; motor: 2.41, 95% CI; 1.59, 3.23; language: 1.37, 95% CI; 0.70,

2.04], stimulation at home [cognitive: 0.21, 95% CI; 0.15, 0.27; motor: 0.12, 95% CI; 0.07,

0.17; language: 0.21, 95% CI; 0.16, 0.25] and number of diarrhoeal episodes [cognitive:

-2.87, 95% CI; -4.34, -1.39; motor: -2.62, 95% CI; -3.93, -1.29; language: -2.25, 95% CI;

-3.32, -1.17] influenced the composite scores in all three domains i.e., cognitive, language

and motor. While increase in LAZ score and stimulation led to increase in composite scores;

an increase in number of diarrhoeal episodes was associated with decrease in scores.

Weight for height z scores (WHZ) were associated with motor and language but not with

cognitive scores. Additionally, a negative association of birth order with cognitive and lan-

guage scores was noted.

PLOS ONE

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OPEN ACCESS

Citation: Upadhyay RP, Taneja S, Ranjitkar S,

Mazumder S, Bhandari N, Dua T, et al. (2021)

Factors determining cognitive, motor and language

scores in low birth weight infants from North India.

PLoS ONE 16(5): e0251387. https://doi.org/

10.1371/journal.pone.0251387

Editor: Kannan Navaneetham, University of

Botswana, BOTSWANA

Received: October 28, 2020

Accepted: April 22, 2021

Published: May 12, 2021

Peer Review History: PLOS recognizes the

benefits of transparency in the peer review

process; therefore, we enable the publication of

all of the content of peer review and author

responses alongside final, published articles. The

editorial history of this article is available here:

https://doi.org/10.1371/journal.pone.0251387

Copyright: © 2021 Upadhyay et al. This is an open

access article distributed under the terms of the

Creative Commons Attribution License, which

permits unrestricted use, distribution, and

reproduction in any medium, provided the original

author and source are credited.

Data Availability Statement: All relevant data are

available from figshare (https://figshare.com/s/

c932d11ff5101e2268bf).

Conclusions

The findings indicate the possible importance of promoting nutrition and preventing diar-

rhoea as well as ensuring optimal stimulation and nurturance at home for enhancing child

development in LBW infants.

Introduction

It is estimated that around 250 million (43%) children under the age of 5 years in low- and

middle-income countries in 2010 did not reach their full developmental potential [1]. The

largest numbers are from Sub-Saharan Africa followed by South Asia [1]. Infants and children

with low birth weight (LBW) i.e. with birth weight�2500 g have been identified to be particu-

larly at a higher risk of neurodevelopmental impairment. Data from available studies suggest

that infants and children born with LBW have a higher risk of lower performance in cognitive,

motor and language domains; sub-optimal academic performance and significant behavioural

problems and developmental delay compared to term healthy counterparts [2–6].

Globally, 20 million LBW babies are born each year, more than 90% of them represent

from developing countries [7]. South Asia alone accounts for around one-fifth of all LBW

babies globally [7,8]. It is important to identify factors that influence neurodevelopment in

these low birth weight individuals especially in the first 2–3 years of life as this is the period

when substantial brain development occurs [9,10]. Such an understanding will not only help

putting together interventions that could accelerate development but also intervene early for

factors that may negatively influence development. Evidence from published studies done in

low-middle-income settings points towards certain biological factors that pose a risk for poor

neurodevelopment in children. These risk factors include prematurity, low birth weight, poor

nutrition, inadequate linear growth reflected as stunting, early childhood illnesses such as diar-

rhoea, poor socio-economic status and low maternal education [11–16]. Responsive stimula-

tion during the first years of life has also been shown to be crucial for later cognitive

development of children [17]. There are, however, limited studies that study the risk factors in

low birth weight infants. It is important to examine whether the risk factors for poor neurode-

velopment vary among normal healthy children and those born with low birth weight. With

this background, the primary objective of the current analysis was to determine the risk and

protective factors for cognitive, language and motor performance in low birth weight infants

from rural Haryana, India.

Materials and methods

Study design, setting and participants

This secondary data analysis used data from an individually randomized controlled trial

(RCT) aimed to evaluate the effect of community-initiated Kangaroo Mother Care (ciKMC)

on neurodevelopmental outcomes of infants born low birth weight at 12 months of corrected

age [18]. A total of 552 stable late preterm or term infants small for gestational age identified

within 72 hours of birth and weighing between 1500–2250 g were included in the trial (Clini-

calTrials.gov identifier NCT02631343) [18]. The study was conducted in rural and semi urban

population in districts Faridabad and Palwal, Haryana. Details of the study areas and the trial

procedures have been published [18].

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Funding: The original study was funded by Grand

Challenges Canada (Grant Number 0725–03) and

the Research Council of Norway (RCN) through its

Centers of Excellence Scheme (project number

223269). This secondary data analysis was

supported by Centre for Intervention Science in

Maternal and Child Health (CISMAC), Norway

(https://www.uib.no/en/cismac). The funding was

recieved by RPU and SR The funders had no role in

study design, data collection and analysis, decision

to publish, or preparation of the manuscript.

Competing interests: The authors have declared

that no competing interests exist.

Participants and data collection

Pregnant women were identified and followed up by study workers through a 3 monthly

household surveillance programme. Babies born at home and also those born in a health facil-

ity were included, if KMC was not initiated in the facility. In case of home delivery, visit by the

team was made at the earliest in order to weigh the baby. In mothers who delivered at a health

facility, study team contacted the mother-infant dyad at home, soon after discharge and

screened the child for enrolment and measured weight, if still inside the 72 hours enrolment

window. Weight of the infant was measured using digital weighing scale (AWS-SR-20; Ameri-

can Weigh Scales, Cumming, GA, USA).

To be eligible for the study, a newborn had to weigh between 1500–2250 g within 72 hours

of delivery. Both singleton and multiple births were eligible. Infants who were unable to feed,

those with breathing problems, those with gross congenital malformations, or who were less

than normally active were referred to hospitals and therefore, not included in the study [18].

Written informed consent in the local language was obtained from caregivers by a study

worker prior to enrolment of participants. The intervention comprised of promotion and sup-

port of skin-to-skin contact and exclusive breastfeeding. Mother-infant dyads allocated to the

intervention group were visited at home by a trained intervention delivery team to explain and

initiate KMC and support its practice. All infants in the intervention and control groups

received Home Based Post Natal Care (HBPNC) visits by government health workers (Accred-

ited Social Health Activists; ASHAs) as implemented through the health system [18].

The sample size for the primary trial was calculated based on the expected difference of 0.25

SD (around 3.75 points) for cognitive, language and motor outcomes between the intervention

group and the control group infants [18]. Considering a power of 80% and assuming a 10%

loss to follow up, a total of 552 infants were enrolled. Ethical clearances were obtained from

the Ethics Review Committee, Society for Applied Studies, New Delhi and WHO Ethics

Review Committee. State approvals were available through a Memorandum of Understanding

signed with the National Health Mission in Haryana.

Outcomes

The neurodevelopmental assessment was done by psychologists using Bayley Scales of Infant and

Toddler Development 3rd edition (Bayley-III). The Bayley-III is a comprehensive assessment tool

of developmental functioning in infants and toddlers aged 1–42 months [19]. The test is adminis-

tered directly with the child, takes 40 to 60 minutes to administer and includes three main sub-

scales: cognitive, language (receptive and expressive) and motor (fine and gross) [19]. The

BSID-III was adapted for use in the study setting. Details of the adaptation have been provided

elsewhere [18]. The psychologists were trained and standardized in administering relevant ques-

tionnaires and scales. Periodic re-training and standardization exercises were conducted.

Exposures and other variables

At enrolment, information was collected on household characteristics (social class, religion,

wealth quintile, type of family), infant and birth characteristics (sex, place of delivery, type of

delivery, gestational age, birth order, parity and timing of initiation of breastfeeding) and mater-

nal and paternal characteristics (age, education and paternal occupation). Gestational age was

assessed either through documented records/available ultrasound reports or through self-

reported date of last menstrual period (LMP). Gathering information on vital status, breastfeed-

ing and morbidity (including any hospitalization) along with anthropometric measurements

(weight and length) was done by an independent trained outcome ascertainment team during

their home visits at child age 1, 3, 6 and 12 months. Caregivers were asked about morbidities in

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the previous 2 weeks from the visit. Diarrhoea was operationally defined as three or more loose

stools in a day and pneumonia was defined as presence of difficult and fast breathing.

Data on maternal depressive symptoms was assessed using the Patient Health Question-

naire (PHQ)-9 [20]. The 9 items of PHQ-9 tool are based on the DSM-IV diagnostic criteria

and higher scores reflect presence of depressive symptoms. To measure infant temperament,

infant temperament scale was used as adapted in the MAL-ED study [21]. This 47 item-scale

covered six domains i.e. activity, positive emotionality, negative emotionality, sociability,

attention and soothability where higher scores reflect more difficult temperament. Maternal

sense of competence was assessed using “maternal self-efficacy scale” that consists of 10 ques-

tions with four-point scale responses: higher scores reflecting better maternal self-efficacy [22].

Maternal postnatal attachment scale was used to assess mother-infant bonding. This scale con-

sists of 19 items with higher scores reflecting better bonding [23]. PROCESS (Pediatric Review

of Children’s Environmental Support and Stimulation) questionnaire was used to assess the

intensity of stimulation at home. It consisted of three components: clinical observation, parent

questionnaire and toy list. Higher scores reflect better stimulation and support to infant [24].

Statistical analysis

All analysis was done using STATA version 16.0. The normality of the data was examined

using histogram, skewness and kurtosis coefficient. Mean (SD; standard deviation) or median

(IQR; inter-quartile range) were calculated for continuous variables depending upon the

nature of distribution and proportions for categorical variables. Distribution of baseline char-

acteristics was presented. The composite BSID-III scores for cognitive, motor and language

domains were calculated.

Potential variables for inclusion in the univariate model were determined from previous lit-

erature. Out of these variables, some were selected for inclusion in the final prediction model

based on the method suggested by Hosmer and Lemeshow (Applied logistic regression, Sec-

ond Edition) [25]. For each of the three outcomes i.e., cognitive, language and motor compos-

ite scores, univariable linear regression analysis was done as the initial step. Potential variables

were put in the univariate model and their corresponding p-value was recorded. Two sets of

variables were created- one set containing variable with p-value <0.20 and the other with vari-

able having a p-value�0.20 on univariate linear regression. All those variables for which the

P-value was less than 0.20 were considered for the multivariable regression analysis. Using

stepwise backward method, multivariable regression was done wherein all variables for which

p-value was greater than 0.05 in the model were removed and the regression model was re-

run. This process of model building was continued till the final sets of variables in the multi-

variate model were statistically significant. In the next step, variables that were excluded based

on their p-value of�0.20 on univariable regression or a p-value of�0.05 in multivariable

model were again put in the multivariable regression model one by one. Those that became

statistically significant i.e. p<0.05 were retained in the model. The final multivariate model

consisted of variables that were statistically significant with p-value of<0.05. Generalized

additive model (GAM) plots were generated using R version 3.1.2 (The R Foundation for Sta-

tistical Computing, Vienna, Austria) [26]. Plots were created using mgcv package. The aim of

the GAM plots was to explore nonlinear associations between continuous variables significant

in the multivariate model and the composite cognitive, language and motor scores.

Results

Baseline characteristics of the infants enrolled in the primary trial (N = 552) as well as those

available for neurodevelopmental assessments at 12 months of corrected age (N = 516) have

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been presented in Table 1. Majority of the infants included in this analysis were born to Hindu

families (81.9%) and resided in joint families (73.8%). Mean (SD) birth weight (in grams) and

gestational age (in weeks) was 2058.7 (165.3) grams and 35.7 (1.9) respectively. Out of the total

infants enrolled, around three-fifth (59.7%) were females. Majority of the infants were of birth

order three or less (82.0%).

Determinants of cognitive scores

Mean (SD) composite cognitive score in the sample was 102.1 (11.8). Findings of the univari-

able regression has been presented in S1 Table. Findings of the multivariable linear regression

have been presented in Table 2. For each unit increase in length for age z score (LAZ), there

was around 2 unit increase in composite cognitive score (adjusted b = 2.19, 95% CI; 1.29,

3.10). PROCESS score was significantly associated with cognitive score at 12 months of age

(adjusted b = 0.21, 95% CI; 0.15, 0.27). With each episode of diarrhoea, there was around

3-point lower composite cognitive score (adjusted b = -2.87, 95% CI; -4.34, -1.39). Infants with

birth order of�4 had around 4 points lower cognitive score compared to those with birth

order of 1 (adjusted b = -3.79, 95% CI; -6.53, -1.05). When birth order was included as a con-

tinuous variable in the model, there was a significant association with cognitive scores i.e.,

with each unit increase in birth order, the cognitive composite scores reduced by 0.95 unit

(adjusted b = -0.95, 95% CI; -1.57, -0.32). These four significant variables in the multivariable

linear regression model explained around 22.8% of the variation in composite cognitive score.

Fig 1 shows the GAM plots. The plots re-affirm the associations observed on multivariable lin-

ear regression.

Determinants of language scores

Mean (SD) composite language score in the sample was 84.9 (9.1). Findings of the univariable

regression has been presented in S1 Table. In the multivariable regression model, each unit

increase in LAZ score (adjusted b = 1.37, 95% CI; 0.70, 2.04) and weight for height Z score

(WHZ) (adjusted b = 0.91, 95% CI; 0.16, 1.65) were associated with increase composite lan-

guage score (Table 2). With each unit increase of PROCESS score, the composite language

score increases by 0.21 units (95% CI, 0.16, 0.25). Compared to infants with birth order of 1,

those with birth order of 2 to 3 (adjusted b = -1.69, 95% CI; -3.17, -0.19) and�4 (adjusted b =-2.62, 95% CI; -4.63, -0.61) had lower language score (Table 2). When birth order was included

as a continuous variable in the model, there was a significant association with language scores

i.e., with each unit increase in birth order, the composite scores reduced by 0.61 unit (adjusted

b = -0.61, 95% CI; -1.06, -0.15). Each episode of diarrhoea led to a 2.25 unit decrease in com-

posite language scores (95% CI, -3.32, -1.17). These variables explained around one-third i.e.

31.1% of variability in the language scores. Fig 2 shows the GAM plots which re-affirm the

associations observed on multivariable linear regression.

Determinants of motor scores

Mean (SD) composite motor score in the sample was 90.2 (10.4). Findings of the univariable

regression has been presented in S1 Table. In the multivariable regression model, each unit

increase in LAZ score, WHZ score and PROCESS score was associated with an increase in the

composite motor score by 2.41 points (95% CI; 1.59, 3.23), 1.09 points (95% CI; 0.19, 2.00) and

0.12 (95% CI; 0.07, 0.17) respectively (Table 2). Each episode of diarrhoea was associated with

a decrease in the motor score by 2.62 points (95% CI; -3.93, -1.29). Overall, these variables

explained around 19% of the variability in the composite motor scores. Fig 3 shows the GAM

plots which re-affirm the associations observed on multivariable linear regression.

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Table 1. Baseline characteristics of the primary trial population and the sample included in this secondary data analysis.

Variables Number (%) (N = 552) Number (%) (N = 516)

HOUSEHOLD CHARACTERISTICS

Quintiles

1 (Least poor) 110 (19.9) 109 (21.1)

2 112 (20.4) 105 (20.3)

3 110 (19.9) 99 (19.2)

4 110 (19.9) 100 (19.4)

5 (Poorest) 110 (19.9) 103 (20.0)

Religion

Hindu 450 (81.5) 423 (81.9)

Muslim 98 (17.8) 89 (17.3)

Others¶ 4 (0.7) 4 (0.8)

Social class£

General 137 (24.8) 133 (25.8)

Other Backward Class (OBC) 181 (32.8) 167 (32.4)

Scheduled Caste/Tribe (SC/ST) 234 (42.4) 216 (41.8)

Type of family

Nuclear 140 (25.4) 135 (26.2)

Joint 412 (74.6) 381 (73.8)

MATERNAL AND PATERNAL CHARACTERISTICS

Mean maternal age (years; SD) 23.0 (3.7) 23.1 (3.8)

Median years of education of mother (IQR) 5 (0–9) 5 (0–9)

Mother’s occupation

Employed outside home 10 (1.8) 9 (1.7)

Home maker 542 (98.2) 507 (98.3)

Mean father’s age (years; SD) 26.4 (4.8) 26.4 (4.7)

Median years of education of father (IQR) 8 (5–12) 8 (5–12)

Father’s occupation

Employed in a government/private firm 225 (40.8) 212 (41.1)

Daily wage earner 126 (22.8) 116 (22.5)

Self-employed (own business/farming) 177 (32.1) 166 (32.1)

Unemployed 24 (4.3) 22 (4.3)

BIRTH RELATED CHARACTERISTICS

Place of delivery

Home 160 (29.0) 148 (28.7)

Government facility 283 (51.3) 266 (51.5)

Private facility 109 (19.7) 102 (19.8)

Type of delivery

Normal 546 (98.9) 511 (99.0)

Caesarean section 6 (1.1) 5 (1.0)

Birth order

1 206 (37.3) 191 (37.0)

2–3 244 (44.2) 232 (45.0)

�4 102 (18.5) 93 (18.0)

Parity

Primiparous 206 (37.3) 191 (37.0)

Multiparous 346 (62.7) 325 (63.0)

INFANT CHARACTERISTICS

(Continued)

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Discussion

The current analysis was done to examine the factors that may determine cognitive, motor and

language scores in low birth weight infants at 12 months of corrected age. We found that linear

growth, child stimulation at home and number of diarrhoeal episodes were associated with all

three domains of Bayley-III i.e. cognitive, language and motor. While increase in linear growth

(represented by LAZ score) and child stimulation (indicated by PROCESS scores) was associ-

ated with increase in composite scores; an increase in number of diarrhoeal episodes was asso-

ciated with decrease in scores. Additionally, we observed a negative association of birth order

with cognitive and language scores.

Studies from Asia and Africa have shown association between anthropometric measures of

growth with neurodevelopmental outcomes in children, especially the length for age–Z scores

[27–29]. In a recent study conducted among young north Indian children, linear growth, child

Table 1. (Continued)

Variables Number (%) (N = 552) Number (%) (N = 516)

Sex of the baby

Male 229 (41.5) 208 (40.3)

Female 323 (58.5) 308 (59.7)

Mean birth weight (grams; SD) 2058.6 (167.0) 2058.7 (165.3)

Mean gestational age (weeks; SD) 35.6 (1.9) 35.7 (1.9)

Early initiation of breastfeeding (within an hour of birth) present 341 (61.8) 323 (62.6)

Exclusive breastfeeding at 3 months� 250 (48.7) 239 (48.4)

¶Others: Christian/Sikh/Jain/Parsi/Zoroastrian/Buddhist/neo Buddhist

£General- group that do not qualify for any of the positive discrimination schemes by Government of India (GOI), OBC- term used by the Government of India to

classify castes which are socially and educationally disadvantaged, SC/ST- official designations given to groups of historically disadvantaged indigenous people in India

�data available for 513 infants among the overall study infants and for 494 infants in the sample for this analysis; SD- standard deviation; IQR- Inter-quartile range.

https://doi.org/10.1371/journal.pone.0251387.t001

Table 2. Determinants of cognitive, language and motor scores, using multivariable linear regression, at 12 months of age in low birth weight infants from rural

Haryana (N = 516).

Variables Cognitive score† Language score † Motor score ¶

Standardized ẞ-coefficient (95%CI)

P-value Standardized ẞ-coefficient (95%CI)

P-value Standardized ẞ-coefficient (95%CI)

P-value

WHZ at 12 months ----- ----- 0.91 (0.16, 1.65) 0.017� 1.09 (0.19, 2.00) 0.018�

Birth order

1 Ref Ref

2–3 -1.51 (-3.56, 0.54) 0.024�£ -1.69 (-3.17, -0.19) 0.018�£ ----- -----

�4 -3.79 (-6.53, -1.05) -2.62 (-4.63, -0.61)

LAZ at 12 months 2.19 (1.29, 3.10) <0.001� 1.37 (0.70, 2.04) <0.001� 2.41 (1.59, 3.23) <0.001�

PROCESS Score at 12

months

0.21 (0.15, 0.27) <0.001� 0.21 (0.16, 0.25) <0.001� 0.12 (0.07, 0.17) <0.001�

No. of episodes of

“Diarrhoea”

-2.87 (-4.34, -1.39) <0.001� -2.25 (-3.32, -1.17) <0.001� -2.62 (-3.93, -1.29) <0.001�

†Adjusted R2 of the multivariable model = 22.8%

† Adjusted R2 of the multivariable model = 31.1%

¶ Adjusted R2 of the multivariable model = 18.9%

� denotes statistical significance£P-value calculated based on likelihood ratio.

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stimulation and diarrhoeal episodes were associated with scores obtained on Ages and Stages

Questionnaire- 3rd edition (ASQ-3) [30]. Owing to the overlap in the factors that are responsi-

ble for poor growth and neurodevelopment in early childhood, such as inadequate nutrition;

morbidities and insufficient care and stimulation, linear growth and neurodevelopment seem

to be often closely associated [31]. These adversities lead to deficits in neuronal growth and

connectivity within regions of the brain associated with memory, high order learning and

motor functioning [32,33]. Stunting, reflecting malnutrition, is a commonly used indicator to

identify children with higher risk of developmental deficits [1,34]. We have shown in our anal-

ysis that LAZ is a significant determinant of neurodevelopment and support its use as a proxy

for neurodevelopment during infancy.

We observed that weight for height z scores (WHZ) were associated with motor and lan-

guage outcomes. It could be because children who do not experience acute malnutrition possi-

bly have an enhanced capability to engage with the surrounding environment which is

Fig 1. Association between length for age z-scores (LAZ); PROCESS score and birth order with change in composite cognitive score. The graphs were constructed

using generalized additive models in R, the solid line depicts the association of composite cognitive score and HAZ/PROCESS score/birth order. The Y-axis is centered

on the mean composite cognitive score. The shaded area spans the 95% confidence interval of this association.

https://doi.org/10.1371/journal.pone.0251387.g001

Fig 2. Associations between height for age z-scores (HAZ); weight for height z-scores (WHZ), birth order, PROCESS score and change in composite language

score. The graphs were constructed using generalized additive models in R, the solid line depicts the association of composite language score and HAZ/WHZ/birth

order/PROCESS score. The Y-axis is centered on the mean composite language score. The shaded area spans the 95% confidence interval of this association.

https://doi.org/10.1371/journal.pone.0251387.g002

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essential for development [35,36]. Studies have found an association of WAZ with cognitive

outcomes; however, we did not find any significant association [35,37]. Our findings are simi-

lar to a prospective study in Peruvian children that noted no significant association between

weight for length z scores (WLZ) during infancy and intelligence at child age 9 years. [38]. It

may be worth to explore whether there is, in real, any differential effect of acute malnutrition

on brain functioning.

Similar to our findings, previous studies have also documented a significant negative effect

of diarrhoea on neurodevelopmental outcomes [30,38–41]. There are indications that this

could be both through its negative impact on growth and its independent effect on gut envi-

ronment. Intestinal damage as a result of diarrhoea could hamper absorption of critical growth

promoting nutrients, thereby affecting linear growth and in turn cognition [41]. On the other

hand, occurrence of diarrhoea may instigate systemic inflammatory signals and release of

potential neural damaging cytokines [42,43]. Another concept is that of “functional isolation”

wherein a child with diarrhoea may be irritable and therefore receive less quality responsive

care from the caregivers [44]. In concordance with previous studies showing that children

with higher birth order positions are at a disadvantage in terms of cognitive development and

educational attainment, we found a negative association of birth order with cognitive and lan-

guage scores [45–47]. A plausible explanation to justify this association comes from the quan-

tity and quality dilution hypothesis [47]. According to the dilution model, children who are

early in the birth order often get a reasonably larger proportion of the family resources or the

quality of care received is often better than those who are later in the birth order (who probably

have to face more competition). This is considered beneficial for the development of children

born early in the birth order [47].

The findings of our study provide impetus to focus on reduction of stunting during infancy,

possibly through improved nutrition. The findings also lay emphasis on promotion of early

child stimulation interventions and diarrhoea prevention and management during infancy.

The study identifies important factors that influence cognitive, language and motor outcomes

in low birth weight infants during infancy and could serve as indicators to identify those that

need additional care and support.

Fig 3. Associations between height for age z-scores (HAZ); weight for height z-scores (WHZ), PROCESS score and change in composite motor score. The graphs

were constructed using generalized additive models in R, the solid line depicts the association of composite motor score and HAZ/WHZ/PROCESS score. The Y-axis is

centered on the mean composite motor score. The shaded area spans the 95% confidence interval of this association.

https://doi.org/10.1371/journal.pone.0251387.g003

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Strengths and limitations

The modest sample size of around 500 infants is one of the main strengths. Trained and stan-

dardized psychologists conducted the Bayley-III assessments and collected data on stimulation

practices at home. The standardized and reliable measurement of anthropometry by trained

study team members is also a strength. Another strength is the robustness of the multivariable

model for the outcomes considered in the analysis, as reflected by the R2 values. One key limi-

tation is that the study subjects for this analysis were largely stable late preterm or term infants

small for gestational age and were only slightly low birth weight. Therefore, the findings may

only be applicable to this specific subset of infants. However, for this subset of LBWs, the find-

ings could be generalizable to other South-east Asian and low-middle-income countries as the

burden of low birth weight, risk factors for poor development and the quality of care provide

to these vulnerable infants is similar in these settings. It should also be noted from Fig 3 that

the association between WHZ and composite motor scores may not be linear. Therefore, it

would have been more appropriate to include WHZ as quadratic or logarithmic or exponential

term or in other transformed form to achieve linearity for regression analysis. However,

because such terms are difficult to interpret and communicate, we chose to include it as linear

term in addition to showing the shape of association in Fig 3.

Conclusions

The findings support promoting nutrition and ensuring optimal stimulation at home for

advancing child development in infants born with low birth weight. Our study also lends sup-

port for diarrhoea disease control as it is an important risk factor for poor neurodevelopment

in these vulnerable infants.

Supporting information

S1 Table. Findings on univariable linear regression for cognitive, language and motor

scores at 12 months of infant age in low birth weight infants from rural Haryana.

(DOC)

Author Contributions

Conceptualization: Ravi Prakash Upadhyay, Sunita Taneja, Suman Ranjitkar, Tor A. Strand.

Data curation: Ravi Prakash Upadhyay, Sunita Taneja.

Formal analysis: Ravi Prakash Upadhyay, Sunita Taneja, Suman Ranjitkar, Tor A. Strand.

Funding acquisition: Ravi Prakash Upadhyay, Suman Ranjitkar.

Investigation: Ravi Prakash Upadhyay, Tor A. Strand.

Methodology: Ravi Prakash Upadhyay, Tor A. Strand.

Project administration: Sunita Taneja, Sarmila Mazumder, Nita Bhandari.

Resources: Sunita Taneja, Sarmila Mazumder, Nita Bhandari.

Supervision: Sarmila Mazumder, Nita Bhandari, Tarun Dua.

Writing – original draft: Ravi Prakash Upadhyay, Tor A. Strand.

Writing – review & editing: Ravi Prakash Upadhyay, Sunita Taneja, Suman Ranjitkar, Sarmila

Mazumder, Nita Bhandari, Tarun Dua, Laxman Shrestha, Tor A. Strand.

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